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Preventable Readmissions

Preventable Readmissions

Preventable Readmissions

An acute care hospital is facing challenges related to an increased number of preventable readmission. Describe the role of analytics in reducing the number of preventable readmissions. Which analytics would be important? How do analytics help to identify patients who are at risk for preventable readmissions?

Preventable Readmissions

Preventable Readmissions
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Preventable Readmissions
Hospital readmission is a situation that occurs when a discharged patient from a hospital gets readmitted again after a short interval of time. Some of these cases are very much preventable if a health care facility has a better analytical system to keep their patient’s indexes organized. Analytics play a significant role in reducing the number of avoidable readmissions. There have been increased demands on accountable care risk, and this has forced the health care facilities to adopt the newly advanced analytics at a faster rate.
In reducing the number of preventable readmissions, the analytic prioritizes which health conditions should be considered for the prevention of readmission. It assists in identifying the patients that are a risk on an everyday basis and, at the same time, picks those that are susceptible to preventable readmission (Preventing hospital readmissions, 2019). The analytics also assist in moving to proactive preventable readmission from a traditional reactive model. Applying this method also provides the prevention services of possible personal readmissions.
The essential\l type of analytic that would be necessary for a healthcare facility is the diagnostic analytic. This analytic describes the methods that one applies when collecting their data. It answers the W’s questions (What is diagnostic analytics, 2020). Diagnostic analytics also majors at looking into the reasons for different results. In this case, it can be applied to look into the reasons behind preventable readmissions.
Analytics tracks down and identifies patients at risk of preventable readmission by using the data already present in the electronic health record to group each patient’s level of risk. This program calculates the score of readmissions for every patient, thus determining their risks (Roles of analytics in preventing readmissions, 2015).

Preventing hospital readmissions: Analytics and care management. (2019, April 26). Health Catalyst.
What can we predict? The role of advanced analytics in reducing readmissions. (2015, 25). Healthcare Innovation.
What is diagnostic analytics? Explanation & examples. (2020, August 4). Sisense.

Preventable Readmissions

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